The applications and limitations of using remote sensing platforms to detect harvest activity

Abstract

Multispectral remote sensing applications that detect changes in vegetative reflectance in the near infrared are used to identify forest cover change in forests across the globe. Remote sensing platforms are used to identify changes in vegetative density often using the NDVI (Normalized Difference Vegetative Index) or other similar methods based a change of vegetative reflectance over time. Changes in forest cover may represent any number of disturbance events, fire, hurricane damage, human harvest behavior, and land use change. This paper aims to develop an accuracy assessment of using remote sensing products that identify indiscriminate changes in vegetative density to identify human harvest activity across multiple geophysical regions and forest cover types in the Southeastern United States.